Retailers hit by ‘Christmas Returns Hangover’ surge

Retailers are facing a significant operational strain in the weeks following Christmas, as a surge in product returns and customer enquiries slows support teams and adds costs that can erode holiday profits.

New analysis of millions of post-holiday customer interactions shows that return requests rise sharply from late December, triggering delays in customer service and creating risks for customer retention. The data points to a period where the volume of returns and enquiries places sustained pressure on retail operations.

The data indicates a 45% increase in return requests in the immediate post-Christmas period. This rise begins straight after Christmas Day and continues into January, when many retailers are already shifting focus away from peak trading.

Returns generate a higher workload than standard orders. Each request often requires customer communication, processing, and coordination across fulfilment and finance teams. When returns rise at this scale, support teams struggle to maintain previous service levels.

Alongside returns, the number of overall support requests increases by 34%. These enquiries include questions about refunds, exchanges, delivery status, and product issues. The combined effect significantly raises the demand placed on customer support teams.

As workloads increase, the time taken to resolve customer issues also rises. Average resolution times are reported to increase by around 28% during the busiest returns period. This slowdown reflects capacity constraints rather than a reduction in service effort.

Longer response times can affect customer satisfaction, particularly when customers are seeking refunds or replacements. Delays may also lead to repeated follow-up contacts, which further increase support volumes and compound the pressure on teams.

The data suggests that the post-holiday period creates a cycle where high demand and slower responses reinforce each other, making it harder for retailers to recover service levels quickly.

The operational impact of post-holiday returns is often underestimated. While holiday sales figures are closely tracked, the cost of managing returns and related support activity is less visible.

Slower resolution times translate into higher staffing costs, whether through overtime, temporary hires, or backlogs that spill into later weeks. These costs can reduce the net profit generated during the holiday trading period.

There is also a longer-term cost associated with customer dissatisfaction. Customers who experience delays or poor communication during returns may be less likely to shop again, affecting future revenue.

Certain product categories account for a disproportionate share of post-holiday issues. Gift sets generate a high volume of returns, often because they do not meet recipient preferences. Clothing returns are driven by size and fit issues, which are common during gift-giving seasons.

Electronics also feature prominently among return requests. These items often require more complex handling, including troubleshooting, testing, or warranty-related queries. This adds further strain on support teams already dealing with high volumes.

The concentration of returns in these categories means retailers operating heavily in these segments face higher operational risk during the post-holiday period.

Despite the recurring nature of post-Christmas returns, many retailers still treat the period as an extension of standard operations rather than a distinct peak. This can result in insufficient staffing, limited automation, or unclear customer communication around returns and refunds.

The data suggests that retailers who fail to plan for the surge risk seeing holiday revenue offset by higher costs and weaker customer relationships. Anticipating demand allows teams to allocate resources more effectively and set realistic expectations for customers.

Clear communication around return policies, processing times, and refund timelines can also reduce the number of follow-up enquiries and help manage customer expectations.

Returns data provides insight into customer behaviour and operational weaknesses. Patterns in return reasons, product categories, and timing can inform future inventory planning and product descriptions.

Using this data can also help retailers predict support demand more accurately. Forecasting tools and historical analysis allow teams to prepare for known spikes rather than reacting once backlogs form.

Improved forecasting supports better scheduling, targeted automation, and clearer customer messaging during peak periods.

"The moment the holiday shopping rush ends, the real pressure starts. Our data shows a near fifty percent spike in return requests, which stretches support teams and quietly reduces the profit retailers worked hard to earn. The smart retailers are not reacting to this. They are preparing for it. Using returns data to predict demand, strengthen operations and set clear customer expectations is how retailers protect margin and hold on to their customers," said Gareth Cummings, CEO, eDesk.